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Test Data (1111_100)
magnific0 edited this page Feb 25, 2014
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1 revision
Trials: 200 - Population size: 100 - Generations: 500
Testing problem: Schwefel, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 0.00205522221586
Mean: 327.762924026
Std: 144.824399158
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000566397917282
Mean: 0.00498374877756
Std: 0.00447634787979
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 2.50111042988e-13
Std: 4.06102369641e-13
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 3.63797880709e-12
Mean: 8.50086507853e-10
Std: 1.6862323669e-09
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0261199081906
Mean: 378.978014326
Std: 172.071894754
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 1.49744691953e-05
Mean: 4.11356440554e-05
Std: 1.14829550327e-05
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 1.57043237041
Mean: 372.298688102
Std: 164.099771527
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 335.578004005
Mean: 1407.05456271
Std: 380.728163325
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.00097949400697
Mean: 21.3555401404
Std: 42.3934189323
Testing problem: Rastrigin, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 6.50872777896e-09
Mean: 3.3948322344
Std: 1.29408149248
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 1.69639613797
Mean: 4.808601802
Std: 1.17858311968
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 1.39976918945e-14
Std: 3.85131860396e-14
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 0.0
Std: 0.0
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 1.01634246412
Mean: 5.47897642422
Std: 2.30318652697
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 1.88147217273e-06
Mean: 6.68186291556e-06
Std: 2.05988577122e-06
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 0.0584548088852
Mean: 0.334085767106
Std: 0.224694132052
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 0.0
Mean: 8.06911097088
Std: 6.5943902934
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 2.78639652151e-06
Mean: 0.00328301539335
Std: 0.00875248223538
Testing problem: Rosenbrock, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 0.000206095671029
Mean: 2.44025893533
Std: 1.86346140304
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.388388326467
Mean: 1.00559323662
Std: 0.271179970872
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.000176249569178
Mean: 1.92565467216
Std: 1.29850286937
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 3.93092119661
Mean: 5.02320599317
Std: 0.233744322913
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.012604422894
Mean: 0.972904166526
Std: 1.67103268917
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 6.25076100287
Mean: 8.76822581855
Std: 7.56521534194
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 3.94760613105
Mean: 38.755420897
Std: 45.1268930813
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 3.51043102823e-29
Mean: 0.0398657911235
Std: 0.396659613382
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.0861168898594
Mean: 0.591588391078
Std: 0.275691391995
Testing problem: Ackley, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 2.82785674877e-08
Mean: 1.52329615819e-07
Std: 8.98017934704e-08
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000200157785792
Mean: 0.000436165595026
Std: 0.000115569626326
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 2.05954808763e-10
Mean: 7.345879105e-10
Std: 2.62692971917e-10
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 4.4408920985e-16
Mean: 7.46069872548e-16
Std: 9.90786813829e-16
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0356020205276
Mean: 0.0858558442816
Std: 0.0276432950796
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 0.000520574248736
Mean: 0.00100661426895
Std: 0.00014742624546
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 0.0625095802831
Mean: 0.294009664969
Std: 0.116304845834
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 3.99680288865e-15
Mean: 1.44962242108
Std: 4.61157030417
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 8.97016690833e-05
Mean: 0.000446224910416
Std: 0.000220355183872
Testing problem: Griewank, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 3.14093195897e-11
Mean: 0.0244461635342
Std: 0.0122224174543
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.105327881292
Mean: 0.201373792302
Std: 0.0404073148151
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 2.20672299323e-08
Mean: 0.000192784163704
Std: 0.000459078704523
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 3.33066907388e-18
Std: 3.31397388567e-17
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0830274582354
Mean: 0.326884979896
Std: 0.128816224154
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 1.81629780814e-05
Mean: 0.00285954256297
Std: 0.00430645957571
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 0.178730303859
Mean: 0.839104446909
Std: 0.215682573548
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 0.0
Mean: 0.00522132840254
Std: 0.00835376045034
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 4.51276300617e-06
Mean: 0.00493398440584
Std: 0.00571616729784
Testing problem: Levy5, Dimension: 10
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -4411.52282082
Mean: -4045.68952045
Std: 236.10299422
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -3468.25134942
Mean: -2871.94994959
Std: 228.823441431
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -4411.51353215
Mean: -4392.61634063
Std: 20.0168177899
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: -4411.52293549
Mean: -4390.15059882
Std: 26.900372043
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -4291.59008067
Mean: -3593.37824295
Std: 401.318014918
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -4411.48704967
Mean: -4402.74842105
Std: 55.953057639
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: -4266.92565148
Mean: -3746.75955221
Std: 400.49454367
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: -4113.00700325
Mean: -1842.38180544
Std: 2595.02286103
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -4390.48967443
Mean: -4211.10075728
Std: 71.4228006666
Testing problem: Cassini 1, Dimension: 6
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 4.98440653684
Mean: 8.71836863709
Std: 2.83685202293
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 5.12689635818
Mean: 5.61631875172
Std: 1.29871276756
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 5.07744693713
Mean: 5.80262587253
Std: 1.17318376439
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 5.42136153976
Mean: 6.88333483554
Std: 1.20746765188
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 4.96954938356
Mean: 15.0308889959
Std: 8.57641856088
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 5.32303158407
Mean: 11.0702883602
Std: 4.06217638052
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 5.54206845308
Mean: 15.754508699
Std: 5.68209874636
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 5.30342237192
Mean: 16.7109623646
Std: 8.09993200005
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 5.83961522458
Mean: 9.68740130537
Std: 2.19591381869
Testing problem: GTOC_1, Dimension: 8
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -1328466.32843
Mean: -779482.327903
Std: 181882.111565
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -853530.760605
Mean: -424737.197926
Std: 125586.682029
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -894162.927735
Mean: -587990.682275
Std: 121003.468637
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: -896462.99538
Mean: -609801.459525
Std: 114359.649954
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -753063.380089
Mean: -100924.280675
Std: 158689.501229
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -1095707.473
Mean: -856765.409669
Std: 133943.107454
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: -746075.483499
Mean: -162970.140012
Std: 213164.838785
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: -1027873.22939
Mean: -196842.741175
Std: 271900.879669
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -1121212.85929
Mean: -529225.872093
Std: 161562.629492
Testing problem: Cassini 2, Dimension: 22
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 11.5128563243
Mean: 18.5896981347
Std: 2.79074546942
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 19.3312280463
Mean: 26.6207530792
Std: 2.11260902906
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 15.7096523056
Mean: 22.2943011251
Std: 2.31667552784
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 13.5927468975
Mean: 20.1346676379
Std: 2.65156837862
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 9.80276320468
Mean: 21.6080505763
Std: 4.74088726469
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 11.8973630336
Mean: 18.3004948172
Std: 3.32245122598
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 15.6854326684
Mean: 25.5492172238
Std: 3.60683831943
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 14.5154836788
Mean: 23.0639808118
Std: 4.0294207105
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 15.419608534
Mean: 22.6889153485
Std: 2.81236851881
Testing problem: Messenger full, Dimension: 26
With Population Size: 100
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 10.4604084257
Mean: 16.4837182911
Std: 1.9329026246
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 17.3776360465
Mean: 25.7043556669
Std: 2.62422176112
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 16.275595457
Mean: 22.1116264466
Std: 2.50446665574
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
Best: 12.1816718553
Mean: 20.2223063233
Std: 2.42822796824
Algorithm name: Simulated Annealing (Corana's) - iter:50000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 10.5147360404
Mean: 19.8254207751
Std: 6.65573775257
Algorithm name: Improved Harmony Search - iter:50000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 16.8455740393
Mean: 20.9961792144
Std: 2.00579686534
Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL
Best: 11.6657583227
Mean: 21.7001996927
Std: 4.44253309599
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
Best: 12.4265547068
Mean: 21.1258255831
Std: 7.78486737198
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 16.8112198822
Mean: 23.9751787506
Std: 3.15124305499